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Petar Žuvela

Showing results (1-10 of 22) with videos related to

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Journal of Computational Chemistry|February 6, 2018
Interpretation of ANN-based QSAR models for prediction of antioxidant activity of flavonoidsPetar Žuvela, Jonathan David, Ming Wah Wong
Journal of Chromatography. A|February 1, 2017
Non-target analysis of phospholipid and sphingolipid species in egg yolk using liquid chromatography/triple quadrupole tandem mass spectrometryBogusław Buszewski, Justyna Walczak, Petar Žuvela, et al.
Journal of Chromatography. A|October 13, 2015
Assessment of column selection systems using Partial Least SquaresPetar Žuvela, J Jay Liu, Alina Plenis, et al.
Analytical Chemistry|September 9, 2015
Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithmsPetar Žuvela, J Jay Liu, Katarzyna Macur, et al.
Journal of Pharmaceutical and Biomedical Analysis|February 10, 2016
Exploiting non-linear relationships between retention time and molecular structure of peptides originating from proteomes and comparing three multivariate approachesPetar Žuvela, Katarzyna Macur, J Jay Liu, et al.
Molecules (Basel, Switzerland)|July 10, 2020
Prediction of Chromatographic Elution Order of Analytical Mixtures Based on Quantitative Structure-Retention Relationships and Multi-Objective OptimizationPetar Žuvela, J Jay Liu, Ming Wah Wong, et al.
International Journal of Molecular Sciences|May 15, 2019
Non-Linear Quantitative Structure⁻Activity Relationships Modelling, Mechanistic Study and In-Silico Design of Flavonoids as Potent AntioxidantsPetar Žuvela, Jonathan David, Xin Yang, et al.
Analytical and Bioanalytical Chemistry|March 20, 2024
Cross-column density functional theory-based quantitative structure-retention relationship model development powered by machine learningSargol Mazraedoost, Petar Žuvela, Szymon Ulenberg, et al.
Journal of Chemical Information and Modeling|March 28, 2025
Prediction of Chromatographic Retention Time of a Small Molecule from SMILES Representation Using a Hybrid Transformer-LSTM ModelSargol Mazraedoost, Hadi Sedigh Malekroodi, Petar Žuvela, et al.
International Journal of Molecular Sciences|July 25, 2019
Quantitative Structure-Retention Relationships with Non-Linear Programming for Prediction of Chromatographic Elution OrderJ Jay Liu, Alham Alipuly, Tomasz Bączek, et al.
Pageof 3

Showing results (1-10 of 22) with videos related to

Sort By:
Pageof 3
Journal of Computational Chemistry|February 6, 2018
Interpretation of ANN-based QSAR models for prediction of antioxidant activity of flavonoidsPetar Žuvela, Jonathan David, Ming Wah Wong
Journal of Chromatography. A|February 1, 2017
Non-target analysis of phospholipid and sphingolipid species in egg yolk using liquid chromatography/triple quadrupole tandem mass spectrometryBogusław Buszewski, Justyna Walczak, Petar Žuvela, et al.
Journal of Chromatography. A|October 13, 2015
Assessment of column selection systems using Partial Least SquaresPetar Žuvela, J Jay Liu, Alina Plenis, et al.
Analytical Chemistry|September 9, 2015
Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithmsPetar Žuvela, J Jay Liu, Katarzyna Macur, et al.
Journal of Pharmaceutical and Biomedical Analysis|February 10, 2016
Exploiting non-linear relationships between retention time and molecular structure of peptides originating from proteomes and comparing three multivariate approachesPetar Žuvela, Katarzyna Macur, J Jay Liu, et al.
Molecules (Basel, Switzerland)|July 10, 2020
Prediction of Chromatographic Elution Order of Analytical Mixtures Based on Quantitative Structure-Retention Relationships and Multi-Objective OptimizationPetar Žuvela, J Jay Liu, Ming Wah Wong, et al.
International Journal of Molecular Sciences|May 15, 2019
Non-Linear Quantitative Structure⁻Activity Relationships Modelling, Mechanistic Study and In-Silico Design of Flavonoids as Potent AntioxidantsPetar Žuvela, Jonathan David, Xin Yang, et al.
Analytical and Bioanalytical Chemistry|March 20, 2024
Cross-column density functional theory-based quantitative structure-retention relationship model development powered by machine learningSargol Mazraedoost, Petar Žuvela, Szymon Ulenberg, et al.
Journal of Chemical Information and Modeling|March 28, 2025
Prediction of Chromatographic Retention Time of a Small Molecule from SMILES Representation Using a Hybrid Transformer-LSTM ModelSargol Mazraedoost, Hadi Sedigh Malekroodi, Petar Žuvela, et al.
International Journal of Molecular Sciences|July 25, 2019
Quantitative Structure-Retention Relationships with Non-Linear Programming for Prediction of Chromatographic Elution OrderJ Jay Liu, Alham Alipuly, Tomasz Bączek, et al.
Pageof 3